def test_hash_numpy_arrays(three_np_arrays):
arr1, arr2, arr3 = three_np_arrays
for obj1, obj2 in itertools.product(three_np_arrays, repeat=2):
are_hashes_equal = hash(obj1) == hash(obj2)
are_arrays_equal = np.all(obj1 == obj2)
assert are_hashes_equal == are_arrays_equal
assert hash(arr1) != hash(arr1.T)
def test_hash_numpy_arrays(three_np_arrays):
arr1, arr2, arr3 = three_np_arrays
for obj1, obj2 in itertools.product(three_np_arrays, repeat=2):
are_hashes_equal = hash(obj1) == hash(obj2)
are_arrays_equal = np.all(obj1 == obj2)
assert are_hashes_equal == are_arrays_equal
assert hash(arr1) != hash(arr1.T)
def test_numpy_persistence():
filename = env['filename']
rnd = np.random.RandomState(0)
a = rnd.random_sample((10, 2))
for compress, cache_size in ((0, 0), (1, 0), (1, 10)):
# We use 'a.T' to have a non C-contiguous array.
for index, obj in enumerate(((a,), (a.T,), (a, a), [a, a, a])):
# Change the file name to avoid side effects between tests
this_filename = filename + str(random.randint(0, 1000))
filenames = numpy_pickle.dump(obj, this_filename,
compress=compress,
cache_size=cache_size)
# Check that one file was created per array
if not compress:
nose.tools.assert_equal(len(filenames), len(obj) + 1)
# Check that these files do exist
for file in filenames:
nose.tools.assert_true(
os.path.exists(os.path.join(env['dir'], file)))
# Unpickle the object
obj_ = numpy_pickle.load(this_filename)
# Check that the items are indeed arrays
for item in obj_:
nose.tools.assert_true(isinstance(item, np.ndarray))
# And finally, check that all the values are equal.
nose.tools.assert_true(np.all(np.array(obj) ==
np.array(obj_)))
# Now test with array subclasses
for obj in (
np.matrix(np.zeros(10)),
np.core.multiarray._reconstruct(np.memmap, (), np.float)
):
this_filename = filename + str(random.randint(0, 1000))
filenames = numpy_pickle.dump(obj, this_filename,
compress=compress,
cache_size=cache_size)
obj_ = numpy_pickle.load(this_filename)
if (type(obj) is not np.memmap
and hasattr(obj, '__array_prepare__')):
# We don't reconstruct memmaps
nose.tools.assert_true(isinstance(obj_, type(obj)))
# Finally smoke test the warning in case of compress + mmap_mode
this_filename = filename + str(random.randint(0, 1000))
numpy_pickle.dump(a, this_filename, compress=1)
numpy_pickle.load(this_filename, mmap_mode='r')
def test_numpy_persistence():
filename = env['filename']
rnd = np.random.RandomState(0)
a = rnd.random_sample((10, 2))
for compress, cache_size in ((0, 0), (1, 0), (1, 10)):
# We use 'a.T' to have a non C-contiguous array.
for index, obj in enumerate(((a,), (a.T,), (a, a), [a, a, a])):
# Change the file name to avoid side effects between tests
this_filename = filename + str(random.randint(0, 1000))
filenames = numpy_pickle.dump(obj, this_filename,
compress=compress,
cache_size=cache_size)
# Check that one file was created per array
if not compress:
nose.tools.assert_equal(len(filenames), len(obj) + 1)
# Check that these files do exist
for file in filenames:
nose.tools.assert_true(
os.path.exists(os.path.join(env['dir'], file)))
# Unpickle the object
obj_ = numpy_pickle.load(this_filename)
# Check that the items are indeed arrays
for item in obj_:
nose.tools.assert_true(isinstance(item, np.ndarray))
# And finally, check that all the values are equal.
nose.tools.assert_true(np.all(np.array(obj) ==
np.array(obj_)))
# Now test with array subclasses
for obj in (
np.matrix(np.zeros(10)),
np.core.multiarray._reconstruct(np.memmap, (), np.float)
):
this_filename = filename + str(random.randint(0, 1000))
filenames = numpy_pickle.dump(obj, this_filename,
compress=compress,
cache_size=cache_size)
obj_ = numpy_pickle.load(this_filename)
if (type(obj) is not np.memmap
and hasattr(obj, '__array_prepare__')):
# We don't reconstruct memmaps
nose.tools.assert_true(isinstance(obj_, type(obj)))
# Finally smoke test the warning in case of compress + mmap_mode
this_filename = filename + str(random.randint(0, 1000))
numpy_pickle.dump(a, this_filename, compress=1)
numpy_pickle.load(this_filename, mmap_mode='r')
def test_memory_numpy(tmpdir, mmap_mode):
" Test memory with a function with numpy arrays."
accumulator = list()
def n(l=None):
accumulator.append(1)
return l
memory = Memory(location=tmpdir.strpath, mmap_mode=mmap_mode, verbose=0)
cached_n = memory.cache(n)
rnd = np.random.RandomState(0)
for i in range(3):
a = rnd.random_sample((10, 10))
for _ in range(3):
assert np.all(cached_n(a) == a)
assert len(accumulator) == i + 1
def test_memory_numpy(tmpdir, mmap_mode):
" Test memory with a function with numpy arrays."
accumulator = list()
def n(l=None):
accumulator.append(1)
return l
memory = Memory(location=tmpdir.strpath, mmap_mode=mmap_mode,
verbose=0)
cached_n = memory.cache(n)
rnd = np.random.RandomState(0)
for i in range(3):
a = rnd.random_sample((10, 10))
for _ in range(3):
assert np.all(cached_n(a) == a)
assert len(accumulator) == i + 1
def test_memory_numpy():
" Test memory with a function with numpy arrays."
# Check with memmapping and without.
for mmap_mode in (None, "r"):
accumulator = list()
def n(l=None):
accumulator.append(1)
return l
memory = Memory(cachedir=env["dir"], mmap_mode=mmap_mode, verbose=0)
memory.clear(warn=False)
cached_n = memory.cache(n)
rnd = np.random.RandomState(0)
for i in range(3):
a = rnd.random_sample((10, 10))
for _ in range(3):
yield nose.tools.assert_true, np.all(cached_n(a) == a)
yield nose.tools.assert_equal, len(accumulator), i + 1
def test_memory_numpy():
" Test memory with a function with numpy arrays."
# Check with memmapping and without.
for mmap_mode in (None, 'r'):
accumulator = list()
def n(l=None):
accumulator.append(1)
return l
memory = Memory(cachedir=env['dir'], mmap_mode=mmap_mode, verbose=0)
memory.clear(warn=False)
cached_n = memory.cache(n)
rnd = np.random.RandomState(0)
for i in range(3):
a = rnd.random_sample((10, 10))
for _ in range(3):
yield nose.tools.assert_true, np.all(cached_n(a) == a)
yield nose.tools.assert_equal, len(accumulator), i + 1
def test_hash_numpy():
""" Test hashing with numpy arrays.
"""
rnd = np.random.RandomState(0)
arr1 = rnd.random_sample((10, 10))
arr2 = arr1.copy()
arr3 = arr2.copy()
arr3[0] += 1
obj_list = (arr1, arr2, arr3)
for obj1 in obj_list:
for obj2 in obj_list:
yield assert_equal, hash(obj1) == hash(obj2), np.all(obj1 == obj2)
d1 = {1: arr1, 2: arr1}
d2 = {1: arr2, 2: arr2}
yield assert_equal, hash(d1), hash(d2)
d3 = {1: arr2, 2: arr3}
yield assert_not_equal, hash(d1), hash(d3)
yield assert_not_equal, hash(arr1), hash(arr1.T)
def test_memory_numpy(tmpdir):
" Test memory with a function with numpy arrays."
# Check with memmapping and without.
for mmap_mode in (None, 'r'):
accumulator = list()
def n(l=None):
accumulator.append(1)
return l
memory = Memory(cachedir=tmpdir.strpath, mmap_mode=mmap_mode,
verbose=0)
memory.clear(warn=False)
cached_n = memory.cache(n)
rnd = np.random.RandomState(0)
for i in range(3):
a = rnd.random_sample((10, 10))
for _ in range(3):
assert np.all(cached_n(a) == a)
assert len(accumulator) == i + 1
def test_hash_numpy():
""" Test hashing with numpy arrays.
"""
rnd = np.random.RandomState(0)
arr1 = rnd.random_sample((10, 10))
arr2 = arr1.copy()
arr3 = arr2.copy()
arr3[0] += 1
obj_list = (arr1, arr2, arr3)
for obj1 in obj_list:
for obj2 in obj_list:
yield nose.tools.assert_equal, hash(obj1) == hash(obj2), \
np.all(obj1 == obj2)
d1 = {1: arr1, 2: arr1}
d2 = {1: arr2, 2: arr2}
yield nose.tools.assert_equal, hash(d1), hash(d2)
d3 = {1: arr2, 2: arr3}
yield nose.tools.assert_not_equal, hash(d1), hash(d3)
yield nose.tools.assert_not_equal, hash(arr1), hash(arr1.T)
